Based on the calculated loss, the parameters in the quantum generator are tuned by computing the analytic quantum gradient descent [1]}, while the discriminator is optimized in the exactly same way as in classical GAN. Further details on the method used for analytic quantum gradient are explained in Ref. [2]}, [3]}.
